Mastercard Logo

Mastercard

Associate Managing Consultant, Advisors & Consulting Services, GenAI Engineer (12 months fixed term)

Posted Yesterday
Be an Early Applicant
Hybrid
Singapore
Mid level
Hybrid
Singapore
Mid level
The role involves designing, building, and deploying applications using Generative AI and LLMs, focusing on project milestones and user prototypes.
The summary above was generated by AI
Our Purpose
Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we're helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.
Title and Summary
Associate Managing Consultant, Advisors & Consulting Services, GenAI Engineer (12 months fixed term)
Overview:
Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience. We provide strategic advisory and execution services, leveraging expertise, data-driven insights, and GenAI-enabled delivery to accelerate innovation and growth. Our Advisors & Consulting Services team combines traditional management consulting with Mastercard's rich data assets, proprietary platforms, and technologies to provide clients with powerful strategic insights and recommendations. Our teams work with a diverse global customer base across industries, from banking and payments to retail and restaurants.
Job Summary
We are seeking a highly skilled and motivated Generative AI Engineer for a 12-month contract engagement. This project-focused role is centered on leveraging Large Language Models (LLMs) and other generative technologies to design, build, and deploy a specific set of transformative applications, including pioneering work in agentic commerce. You will be responsible for driving the technical execution of key GenAI initiatives throughout the project lifecycle, from backend model development to creating intuitive user-facing prototypes. The ideal candidate is a self-directed expert who can deliver high-quality, production-ready systems within a defined timeframe.
Roles and Responsibilities• End-to-End GenAI Solution Delivery: Take ownership of the design, development, and deployment of sophisticated applications using LLMs, with a clear focus on meeting project milestones and deliverables.• System Architecture & Implementation: Architect and implement robust and scalable GenAI systems for the duration of the project. Key tasks include building Retrieval-Augmented Generation (RAG) pipelines, integrating vector databases, and managing APIs.• Agentic System Development: Develop and refine autonomous agents and multi-agent systems to automate complex processes and meet specific project objectives.• Productionalization & Optimization (LLMOps): Establish and manage CI/CD pipelines for the GenAI applications, ensuring they are performant, cost-effective, and reliable throughout the contract period.• Rapid Prototyping & Demonstration: Build interactive web applications and demos to showcase the capabilities of GenAI models to stakeholders, gather feedback, and validate solutions quickly.• Stakeholder Collaboration: Work effectively with internal teams to understand project requirements, provide expert consultation, demonstrate progress, and ensure the final solution meets business goals.• Documentation & Handover: Create clear technical documentation and facilitate a smooth handover of the developed systems and processes to the full-time team at the conclusion of the contract.
Qualifications• Experience: 4-6 years of professional software engineering experience, with at least 2 years of dedicated, hands-on experience building and deploying solutions using Generative AI and LLMs.• Core GenAI Expertise:
o Demonstrable experience with major LLMs (e.g., GPT series, Claude, Llama) via APIs and open-source libraries like Hugging Face.
o Proven ability to build and optimize Retrieval-Augmented Generation (RAG) systems using frameworks like LangChain or LlamaIndex.
o Hands-on experience with model fine-tuning techniques and understanding of their trade-offs.• Technical Proficiency:
o Demonstrated experience in solution architecture, with the ability to design robust, scalable, and end-to-end AI systems.
o Deep proficiency in Python and relevant AI/ML libraries.
o Strong experience with API development and integration (e.g., RESTful APIs, FastAPI).
o Experience with vector databases (e.g., Pinecone, Chroma, Milvus) and embedding models.
o Solid understanding of cloud platforms (AWS or Azure) and experience deploying AI applications using services like AWS SageMaker, or Azure AI.
o Knowledge of containerization technologies (Docker, Kubernetes) for deploying applications.
o Prototyping & Visualization: Experience building demos and simple UIs using frameworks like Streamlit, Gradio, or Flask/FastAPI. Experience with modern frontend frameworks (e.g., React, Vue) is a significant plus.• Project Delivery & Autonomy: A results-oriented professional with a strong sense of ownership and resourcefulness, capable of working independently to deliver on commitments and manage time effectively to meet project deadlines.• Education: Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field is preferred.• Ability to communicate effectively in English and Mandarin• Eligibility to work in the country where you are applying, as well as apply for travel visas as required by travel needs
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
  • Abide by Mastercard's security policies and practices;
  • Ensure the confidentiality and integrity of the information being accessed;
  • Report any suspected information security violation or breach, and
  • Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.

Top Skills

Ai/Ml Libraries
APIs
AWS
Aws Sagemaker
Azure
Azure Ai
Chroma
Cloud Platforms
Docker
Fastapi
Flask
Generative Ai
Gradio
Kubernetes
Large Language Models
Milvus
Pinecone
Python
React
Restful Apis
Streamlit
Vector Databases
Vue

Mastercard Singapore Office

3 Fraser Street DUO Tower Level 17, Singapore, 189352

Similar Jobs at Mastercard

2 Days Ago
Hybrid
Singapore, SGP
Senior level
Senior level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
As the Manager of Account Management, you will lead client relationships, drive strategic account planning, and manage cross-functional collaborations to ensure client success in the payment solutions sector.
Top Skills: Data AnalysisPayment Technologies
2 Days Ago
Hybrid
Singapore, SGP
Senior level
Senior level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
The Senior Specialist in Product Management will optimize product performance, develop strategies, collaborate across teams, and manage disputes and experiences in the payment sector.
Top Skills: Data AnalyticsFinancial ModelingProduct ManagementSecurity Solutions
Mid level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
The Vice President, Sales role focuses on developing new business opportunities, building pipelines in APAC, and collaborating with various teams to align with Mastercard's strategies.

What you need to know about the Singapore Tech Scene

The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account